| Multi-view clustering via canonical correlation analysis K Chaudhuri, SM Kakade, K Livescu, K Sridharan Proceedings of the 26th annual international conference on machine learning …, 2009 | 737 | 2009 |
| Making gradient descent optimal for strongly convex stochastic optimization A Rakhlin, O Shamir, K Sridharan arXiv preprint arXiv:1109.5647, 2011 | 529 | 2011 |
| Learnability, stability and uniform convergence S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan The Journal of Machine Learning Research 11, 2635-2670, 2010 | 328 | 2010 |
| On the complexity of linear prediction: Risk bounds, margin bounds, and regularization SM Kakade, K Sridharan, A Tewari | 305 | 2008 |
| Better mini-batch algorithms via accelerated gradient methods A Cotter, O Shamir, N Srebro, K Sridharan arXiv preprint arXiv:1106.4574, 2011 | 296 | 2011 |
| Stochastic Convex Optimization. S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan COLT 2 (4), 5, 2009 | 265 | 2009 |
| Smoothness, low noise and fast rates N Srebro, K Sridharan, A Tewari Advances in neural information processing systems 23, 2010 | 235* | 2010 |
| Optimization, learning, and games with predictable sequences A Rakhlin, K Sridharan arXiv preprint arXiv:1311.1869, 2013 | 189 | 2013 |
| Online learning with predictable sequences A Rakhlin, K Sridharan Conference on Learning Theory, 993-1019, 2013 | 185 | 2013 |
| Online optimization: Competing with dynamic comparators A Jadbabaie, A Rakhlin, S Shahrampour, K Sridharan Artificial Intelligence and Statistics, 398-406, 2015 | 158 | 2015 |
| Fast rates for regularized objectives K Sridharan, S Shalev-Shwartz, N Srebro Advances in neural information processing systems 21, 1545-1552, 2008 | 142 | 2008 |
| On the universality of online mirror descent N Srebro, K Sridharan, A Tewari Advances in neural information processing systems, 2645-2653, 2011 | 111 | 2011 |
| Online learning: Random averages, combinatorial parameters, and learnability A Rakhlin, K Sridharan, A Tewari | 99 | 2010 |
| Selective sampling and active learning from single and multiple teachers O Dekel, C Gentile, K Sridharan The Journal of Machine Learning Research 13 (1), 2655-2697, 2012 | 93 | 2012 |
| An information theoretic framework for multi-view learning K Sridharan, SM Kakade | 85 | 2008 |
| Learning kernel-based halfspaces with the 0-1 loss S Shalev-Shwartz, O Shamir, K Sridharan SIAM Journal on Computing 40 (6), 1623-1646, 2011 | 83* | 2011 |
| Learning in games: Robustness of fast convergence DJ Foster, Z Li, T Lykouris, K Sridharan, E Tardos Advances in Neural Information Processing Systems 29, 4734-4742, 2016 | 76 | 2016 |
| Relax and randomize: From value to algorithms A Rakhlin, O Shamir, K Sridharan | 75* | 2012 |
| Online learning: Beyond regret A Rakhlin, K Sridharan, A Tewari Proceedings of the 24th Annual Conference on Learning Theory, 559-594, 2011 | 74 | 2011 |
| Learning exponential families in high-dimensions: Strong convexity and sparsity S Kakade, O Shamir, K Sindharan, A Tewari Proceedings of the thirteenth international conference on artificial …, 2010 | 72 | 2010 |
